{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 分组和聚合练习"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>object</th>\n",
       "      <th>price1</th>\n",
       "      <th>price2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>white</td>\n",
       "      <td>pen</td>\n",
       "      <td>5.56</td>\n",
       "      <td>4.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>red</td>\n",
       "      <td>pencil</td>\n",
       "      <td>4.20</td>\n",
       "      <td>4.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>green</td>\n",
       "      <td>pencil</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>red</td>\n",
       "      <td>ashtray</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>green</td>\n",
       "      <td>pen</td>\n",
       "      <td>2.75</td>\n",
       "      <td>3.15</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   color   object  price1  price2\n",
       "0  white      pen    5.56    4.75\n",
       "1    red   pencil    4.20    4.12\n",
       "2  green   pencil    1.30    1.60\n",
       "3    red  ashtray    0.56    0.75\n",
       "4  green      pen    2.75    3.15"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "col =pd.DataFrame({'color': ['white','red','green','red','green'], \n",
    "                   'object': ['pen','pencil','pencil','ashtray','pen'],\n",
    "                   'price1':[5.56,4.20,1.30,0.56,2.75],\n",
    "                   'price2':[4.75,4.12,1.60,0.75,3.15]})\n",
    "col"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>price1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>green</td>\n",
       "      <td>2.025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>red</td>\n",
       "      <td>2.380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>white</td>\n",
       "      <td>5.560</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   color  price1\n",
       "0  green   2.025\n",
       "1    red   2.380\n",
       "2  white   5.560"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按color进行分组，求平均价格，参数as_index默认为True，表示不添加行索引，如果为False表示添加行索引\n",
    "col.groupby(['color'], as_index=False)['price1'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "color\n",
       "green    2.025\n",
       "red      2.380\n",
       "white    5.560\n",
       "Name: price1, dtype: float64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 和上述等价\n",
    "col['price1'].groupby(col['color']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    white\n",
       "1      red\n",
       "2    green\n",
       "3      red\n",
       "4    green\n",
       "Name: color, dtype: object"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 星巴克案例"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Brand</th>\n",
       "      <th>Store Number</th>\n",
       "      <th>Store Name</th>\n",
       "      <th>Ownership Type</th>\n",
       "      <th>Street Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State/Province</th>\n",
       "      <th>Country</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Phone Number</th>\n",
       "      <th>Timezone</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Latitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>47370-257954</td>\n",
       "      <td>Meritxell, 96</td>\n",
       "      <td>Licensed</td>\n",
       "      <td>Av. Meritxell, 96</td>\n",
       "      <td>Andorra la Vella</td>\n",
       "      <td>7</td>\n",
       "      <td>AD</td>\n",
       "      <td>AD500</td>\n",
       "      <td>376818720</td>\n",
       "      <td>GMT+1:00 Europe/Andorra</td>\n",
       "      <td>1.53</td>\n",
       "      <td>42.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>22331-212325</td>\n",
       "      <td>Ajman Drive Thru</td>\n",
       "      <td>Licensed</td>\n",
       "      <td>1 Street 69, Al Jarf</td>\n",
       "      <td>Ajman</td>\n",
       "      <td>AJ</td>\n",
       "      <td>AE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GMT+04:00 Asia/Dubai</td>\n",
       "      <td>55.47</td>\n",
       "      <td>25.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>47089-256771</td>\n",
       "      <td>Dana Mall</td>\n",
       "      <td>Licensed</td>\n",
       "      <td>Sheikh Khalifa Bin Zayed St.</td>\n",
       "      <td>Ajman</td>\n",
       "      <td>AJ</td>\n",
       "      <td>AE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GMT+04:00 Asia/Dubai</td>\n",
       "      <td>55.47</td>\n",
       "      <td>25.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>22126-218024</td>\n",
       "      <td>Twofour 54</td>\n",
       "      <td>Licensed</td>\n",
       "      <td>Al Salam Street</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>AZ</td>\n",
       "      <td>AE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GMT+04:00 Asia/Dubai</td>\n",
       "      <td>54.38</td>\n",
       "      <td>24.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Starbucks</td>\n",
       "      <td>17127-178586</td>\n",
       "      <td>Al Ain Tower</td>\n",
       "      <td>Licensed</td>\n",
       "      <td>Khaldiya Area, Abu Dhabi Island</td>\n",
       "      <td>Abu Dhabi</td>\n",
       "      <td>AZ</td>\n",
       "      <td>AE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>GMT+04:00 Asia/Dubai</td>\n",
       "      <td>54.54</td>\n",
       "      <td>24.51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Brand  Store Number        Store Name Ownership Type  \\\n",
       "0  Starbucks  47370-257954     Meritxell, 96       Licensed   \n",
       "1  Starbucks  22331-212325  Ajman Drive Thru       Licensed   \n",
       "2  Starbucks  47089-256771         Dana Mall       Licensed   \n",
       "3  Starbucks  22126-218024        Twofour 54       Licensed   \n",
       "4  Starbucks  17127-178586      Al Ain Tower       Licensed   \n",
       "\n",
       "                    Street Address              City State/Province Country  \\\n",
       "0                Av. Meritxell, 96  Andorra la Vella              7      AD   \n",
       "1             1 Street 69, Al Jarf             Ajman             AJ      AE   \n",
       "2     Sheikh Khalifa Bin Zayed St.             Ajman             AJ      AE   \n",
       "3                  Al Salam Street         Abu Dhabi             AZ      AE   \n",
       "4  Khaldiya Area, Abu Dhabi Island         Abu Dhabi             AZ      AE   \n",
       "\n",
       "  Postcode Phone Number                 Timezone  Longitude  Latitude  \n",
       "0    AD500    376818720  GMT+1:00 Europe/Andorra       1.53     42.51  \n",
       "1      NaN          NaN     GMT+04:00 Asia/Dubai      55.47     25.42  \n",
       "2      NaN          NaN     GMT+04:00 Asia/Dubai      55.47     25.39  \n",
       "3      NaN          NaN     GMT+04:00 Asia/Dubai      54.38     24.48  \n",
       "4      NaN          NaN     GMT+04:00 Asia/Dubai      54.54     24.51  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 获取数据\n",
    "data = pd.read_csv('./data/directory.csv')\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Brand</th>\n",
       "      <th>Store Number</th>\n",
       "      <th>Store Name</th>\n",
       "      <th>Ownership Type</th>\n",
       "      <th>Street Address</th>\n",
       "      <th>City</th>\n",
       "      <th>State/Province</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Phone Number</th>\n",
       "      <th>Timezone</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Latitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AD</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AE</th>\n",
       "      <td>144</td>\n",
       "      <td>144</td>\n",
       "      <td>144</td>\n",
       "      <td>144</td>\n",
       "      <td>144</td>\n",
       "      <td>144</td>\n",
       "      <td>144</td>\n",
       "      <td>24</td>\n",
       "      <td>78</td>\n",
       "      <td>144</td>\n",
       "      <td>144</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AR</th>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>100</td>\n",
       "      <td>29</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "      <td>108</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AT</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AU</th>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>0</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Brand  Store Number  Store Name  Ownership Type  Street Address  \\\n",
       "Country                                                                    \n",
       "AD           1             1           1               1               1   \n",
       "AE         144           144         144             144             144   \n",
       "AR         108           108         108             108             108   \n",
       "AT          18            18          18              18              18   \n",
       "AU          22            22          22              22              22   \n",
       "\n",
       "         City  State/Province  Postcode  Phone Number  Timezone  Longitude  \\\n",
       "Country                                                                      \n",
       "AD          1               1         1             1         1          1   \n",
       "AE        144             144        24            78       144        144   \n",
       "AR        108             108       100            29       108        108   \n",
       "AT         18              18        18            17        18         18   \n",
       "AU         22              22        22             0        22         22   \n",
       "\n",
       "         Latitude  \n",
       "Country            \n",
       "AD              1  \n",
       "AE            144  \n",
       "AR            108  \n",
       "AT             18  \n",
       "AU             22  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 按Country进行分组，统计各地区星巴克总量\n",
    "count = data.groupby(['Country']).count()\n",
    "count.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Country'>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 绘制Brand列的柱状图\n",
    "count.Brand.plot(kind='bar', figsize=(20, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_count = count.sort_values(by=['Brand'], ascending=False).head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Country'>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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SCIoAAAAAGARFAAAAACQRFAEAAAAwCIoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJJsIiqpqT1W9a2xfVVU3VNXla/avqwYAAADA9rCZGUU/meSUqrokyUndfV6Ss6rq7PXWNt8+AAAAAMuyUFBUVY9N8rEktyTZl+TqsevaJOdvoAYAAADANrHhoKiqTk7y/UkuG6VTk9w8tm9NsmcDtWPd/qVVtb+q9h88eHCj7QEAAACwoEVmFF2W5EXd/dFx+Y4kp4zt08Ztrrd2F919ZXfv7e69u3fvXqA9AAAAABaxSFD0+CTPqqrrkjw8yVfnyGFk5yQ5kOSmddYAAAAA2CZ2bfQK3X3B4e0RFv3TJNdX1RlJLk5ybpJeZw0AAACAbWIzZz1Ld+/r7kOZFqq+McmF3X37emubuW8AAAAAlmvDM4qOpbtvy5Ezmm2oBgAAAMD2sKkZRQAAAACsDkERAAAAAEkERQAAAAAMgiIAAAAAkgiKAAAAABgERQAAAAAkERQBAAAAMAiKAAAAAEgiKAIAAABgEBQBAAAAkERQBAAAAMAgKAIAAAAgiaAIAAAAgEFQBAAAAEASQREAAAAAg6AIAAAAgCSCIgAAAAAGQREAAAAASQRFAAAAAAyCIgAAAACSCIoAAAAAGARFAAAAACQRFAEAAAAwCIoAAAAASCIoAgAAAGAQFAEAAACQRFAEAAAAwCAoAgAAACCJoAgAAACAQVAEAAAAQBJBEQAAAACDoAgAAACAJIIiAAAAAIZdczfAxp152TVben8Hrnjylt4fAAAAMA8zigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIImgCAAAAIBBUAQAAABAEkERAAAAAIOgCAAAAIAkgiIAAAAABkERAAAAAEkERQAAAAAMgiIAAAAAkgiKAAAAABgERQAAAAAkERQBAAAAMAiKAAAAAEgiKAIAAABgWCgoqqr7V9Ubq+raqnptVZ1cVVdV1Q1Vdfman1tXDQAAAID5LTqj6JuS/FR3PzHJLUm+PslJ3X1ekrOq6uyqumQ9tWUMAgAAAIDN27XIlbr7RWsu7k7ytCQ/My5fm+T8JF+W5Op11N6/SA8AAAAALNem1iiqqvOSnJ7kQ0luHuVbk+xJcuo6a0ff5qVVtb+q9h88eHAz7QEAAACwAQsHRVX1WUlekOQZSe5IcsrYddq43fXW7qS7r+zuvd29d/fu3Yu2BwAAAMAGLbqY9clJXpXk+7r7g0luynQYWZKck+TABmoAAAAAbAMLrVGU5NuSPCLJs6vq2UlemuTpVXVGkouTnJukk1y/jhoAAAAA28BCM4q6+8XdfXp37xv/vSzJviQ3Jrmwu2/v7kPrqS1jEAAAAABs3qIziu6iu2/LkTOabagGAAAAwPw2ddYzAAAAAFaHoAgAAACAJIIiAAAAAAZBEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADAIigAAAABIkuyauwE42pmXXbOl93fgiidv6f0BAADAdmVGEQAAAABJBEUAAAAADIIiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADDsmrsBONGcedk1W3ZfB6548pbdFwAAADufGUUAAAAAJBEUAQAAADAIigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIEmya+4GgNVx5mXXbOn9HbjiyVt6fwAAAKvOjCIAAAAAkphRBLBuZkwBAACrzowiAAAAAJIIigAAAAAYBEUAAAAAJBEUAQAAADAIigAAAABIIigCAAAAYBAUAQAAAJBEUAQAAADAICgCAAAAIEmya+4GANgezrzsmi29vwNXPHlL7w8AALh7ZhQBAAAAkERQBAAAAMAgKAIAAAAgiaAIAAAAgEFQBAAAAEASZz0D4AThrG4AAHD3zCgCAAAAIIkZRQCwErZyxpTZUgAAq0tQBABsa6t+2OCqjw8A2FkERQAA3GMEYQCwswiKAABgQYIwAFaNxawBAAAASGJGEQAAcByrvFC+2WAAxyYoAgAAWDGrHoQZ33IJMllrlqCoqq5K8kVJrunuH5mjBwAAAGDrma24PPfE+LZ8jaKquiTJSd19XpKzqursre4BAAAAgLuaYzHrfUmuHtvXJjl/hh4AAAAAOEp199be4XTY2fO7+91V9cQkj+juK9bsvzTJpePiFyR53xa298AkH9nC+9tqxrezrfL4VnlsifHtdMa3c63y2BLj2+mMb+da5bElxrfTGd/OtdVje0h37z7WjjnWKLojySlj+7QcNaupu69McuVWN5UkVbW/u/fOcd9bwfh2tlUe3yqPLTG+nc74dq5VHltifDud8e1cqzy2xPh2OuPbubbT2OY49OymHDnc7JwkB2boAQAAAICjzDGj6HVJrq+qM5JcnOTcGXoAAAAA4ChbPqOouw9lWtD6xiQXdvftW93DpzHLIW9byPh2tlUe3yqPLTG+nc74dq5VHltifDud8e1cqzy2xPh2OuPbubbN2LZ8MWsAAAAAtqc51igCAAAAYBsSFAEAAACQRFAEAAAAwDDHWc+2jar6nO7+q7H96CT37u43z9zWUlTVDxxvX3f/0Fb2shWq6h8keVKSi7r76+buZ7Oq6kFJvjPJx5P8bHf/zcwtLV1VfUGST3T3n6+p7e3u/TO2tWlVVUmemORjSW5IclmS+yZ5YXd/aM7elqGqLuju3zmq9plJvr27nz9TW0tTVW9JciDJB4/690Pd/anZGluSqjopyeMzPfbeOmqV5F9096tnbW4Jquqbj7evu395K3u5J6z6+FZZVf2HJC/u7o/N3cs9Ye176qPqj+7u6+foaVmq6ku7+w/GdvVY4LWqntLdr5q3u+VY5deGqtqV5ClJ3prkkiQPOLyvu39spraWpqoedVSpk9yy9v31TrbKf5tJUlUvyV3fd26L95wn7GLWVfW8JOd091dV1WWZQoY/TbKru58xb3ebV1XPWXOxk1yY5DFJruvux87T1fJU1clJLsj0e3t8kockeX6St3b3dTO2thRV9eYkv5Tk9CRf2d1Pn7ej5aqqn03yJUk+M8lrk7w/yb9Pcmt3f82cvW1WVf16ko8meWCSz02yP8ltSR7f3Y+esbWlqKpXJvnsJD+c5B1J/nWSf5nkld39vDl7W4aq+twkD8v0fHlBkkclOSnTi/ZD5uxtGcbv72NJTktyS5I/S/LMJL/V3d89Y2tLUVXPXnPxGUlecvhCd//o1ne0XKs+vsOq6oszPf4ekOTWJG/p7j+dtalNqqrvSPLNSX4zyfO7+6PzdrRcVfWWw+8vq+qV3f3Uo+s71VFjO+b2TrfKrw1V9eok70nyc5kefz+Y5JwkT+juJ8zY2lJU1UuPUT4ryTu7+99tdT/Ltsp/m0lSVedl+rzwZTnyvrMyve/8vDl7O5FnFD26u88fHwq+NcmXdvffVdVb525sGbr7uSNMeVqSb0/yJ0ke0d2/P2tjy/ORTCHDC5M8Lsmru/s5n/4qO8rJ3f3yJKmqr527mXvAed39yPEtz4eTvCbJM7v7/TP3tQwP6u5vSJKqeu/hF7Gq2vFvRpKku59aVV+Y5Joku5O8PlOY+XfzdrY0f5jkfkneluSNmQLMP+7uv521q+V5cHc/anwb9+dJXpTp9fCj87a1HGvDkqp6/CqFJ8nqjy9JquqZSZ6T6Tnmr5M8OMn3VtX37OTZG939gqp6YZLnJvlwVf1lpg8D3d3/aN7ulqLWbH/ObF3c8+ruf2RHWuXXhj3d/bVJUlUv7O43JXlTVf3zedtaju7+1mPVq+rtW93LPWSV/zaT5AWZJjz8Yab3nT+eKQz7wJxNJSd2UHTH+AD+tCQ/leRT4/Czk+dtazmq6kczpa3vSfKfMyWw96mqR3X3787a3HI8JMkTMs0oeluSz66q7870reMfzNnYkuyuqm/I9IZkd1V94+Ed3f1r87W1NJ8cIW1leiL8kSSpqjO6+y9n7Wzz7j++HagkH1+zfcq8bS1HVf1QkouTPC/JW5L8xyTXVtVPd/fr5uxtSc5O8uWZZhRdnOmbx7+qqj/r7gvnbGxJ7r3mb/LWTM+fX1RVWYXXhqOm4N9v7WXj2zEuzTTj+9bDhap6QJI3JNmxQVFVXZTku5IcTPIV3f3emVtatvuv+Xu833ie+Ywk95+xp2V50HgfVkn2rHlPtmfGnpZtlV8b3lVVr0tyXZJDVfVdSS5K8vsz9rQ0VXXGMcqfn+ReW93LPeTea55PVu1vM5le8x6a6UiLizLN1P9gprDomCHgVjmRDz17WpIfSPKyTMcDfn6SZyV5XHe/Z8bWlqKqXpVpnZRPZppm+ZRM69289fB04J2squ6T6YH1/u6+ZqzJ9PdJLuzux83b3eZV1fszHTKYTC/a/zfJXyR5+yqsMVVVH0nyBznyzVxnekF7aHd/7myNLUFVvTzJ12Z6Q/KIrHmT3N07Poiuqg9nOs7/k4dLSf5hkr/r7q+arbElqar3Zpqx+Bc56pjx7n7ffJ0tR1V9NNMMvqO/Fe8VOez6TZlmoXxdkt9IcmjsWpXxfTQr/PtLkqp6V5J/k7uO8QXd/eUztLQUVfXGTF/a3eWN9yr87sbhL/fNdOjE6Zkeh29J8n92+vjWLOdw+Hf34ExfVN6wCutiJklVHcz0eWEln1vGGmH3zxTuPS7JzyT5xVWYLVxVb8t0iPwnMn0W+vtM72P2d/dPzNnbMqw5tG7t4+8Lkty4Co+/qvpUpokdf5PpPefh953V3b8wY2sn9Iyiz0/y8kz/Dx46av89yeVJvn6uppbopCTfm+RN3f3nVfXiTN+Q/5N521qaX0ny5iR/NC6/MdP4VmXR5189Ru3zxn+r4ENJfqW7Xzqmkn5TkmdnOoxpp7t3kisyTSU9fCz8wzOtpbUK3pZpxs0nk7w7yU2Z1kn54JxNLdEtKzJz6HjeuQpv+j+NkzIdsnRDkkceb0r+DvauFf/9JdO3/Jceo77TZwvfnuQrc+fnzndmdZ47357pkMHXZAqJPjtTmPI9cza1JM/LFIBdnClkeEim1/i3zNnUkr3n8HNLVf1cd//buRtalqp6WaYvsy4da2S+I1Oo+WtJdvS6mMNfJrkjR9bw+UCSb0vyv+Zsaom+PdNnvCdlNR9/70vyM8f4TPTb87Z1As8oOp6q+u3ufszcfWxWVb29u+8SClXV27r7/Dl6WqZVH9/xVNVbV+FDbFWdmukY41MzBbXvTvLc7p79eNzNqqrf6e4LxvbTuvtXx/Yx/2Z3qqr6rCRPTfItSb4iyfu6+wtnbWoJqurjmdbNulM5K7KOyAkwvuu6e9/R26ti1X9/J4IVfu78vUxnnr1tTe0BSd7Q3UeflWlHqapDObIu5o8medWqLGJ92Kou0p0cee9cVQ9N8l+TPLy7e1XGefj95VFr+Fy5Kmv4rPrjbzt/JjphZxTVXU8lmEwrxJ+01b3cQ95S02me35DpeM7TMq3p885Zu1qe31rx8d1JVV2QaTbYx+fuZUnOSXJlpjfKp2aa3fegqnrQChxvfLxj4d89Z1PLUlWvyPT7+0SmMf16pm+MD8zY1jK9YxXC2E9j1cf3OWvWEjm8nWRl1ndb9d/fyjoBnjvvleQfjw+ra33mHM0s2UMyLedwUaZZtQ9csXUxkzuvw/SgFXvuvG0cevY1mdbEPLWqLpm5p2U6ZYXXl0pW//G3bT8TnbAziuqupxLsJP87yc9390pMAx5PGhdlOh73UKb1bVbh0J4kqz++tarqqUnuk+kU5Ds+LBqPv87qHgv/uCT7Mp0V7Pas0N/mMZ47D1uV392zuvuFc/dxTzkBxne8s1/2iqzvttK/v+Qua/T9/3J2+KypE+C583jjO+5ZmXaqqjq86OwTu/uJc/ezDKv83DnWNX16kpu7+7+NmUXPTPKz3b3jD89a9eeWo63a4287fyY6YYMiAAAAAO7sM+ZuAAAAAIDtQVAEAAAAQBJBEQBAkqSqfriqfreqXltVp23yth5eVQ9fUmsAAFtGUAQAnPDG2VAfnekMk9cmuXSTN/nw8R8AwI6ya+4GAAC2gYuSvKG7u6relORLqurXk5yR5MNJvjXJf0pyXXdfV1XfMq53ZqZTgz86yf2SPCnJd2U6FXOq6und/bixfV2S/5HkS7v7oqp6bpL3dvcrquoHk/xJd79iKwYLAHA8ZhQBACR7ktyaJN39gSQPTvKe7n5Mkvcn+XSnqX1od1+Q5DVJHtvd35fkiiRXHA6JhnOT3NDdF43Lv5zkG8f2RUl+Y1mDAQBYlKAIACA5lOS0JKmqRyb5iSTvGPtuTPKFR/38KWu2f3n8+xdJTv409/Ge7n7N4Qvd/WdJ7ltV+8a+v120eQCAZREUAQAkb0/yhLH9mCSXZZoBlPHvHyX5RJLdo/akNdf92DFu72+T3CdJqqpG7Y5j/NwrkrwkR8ImAIBZCYoAAJLXJ/lAVf1upvWGfinJw6rqd5KcPS6/Psl3VNXPJ/nru7m9Nye5pKrePm7veF6dpJO8bVPdAwAsSXX33D0AAJxwquphSV6a5Be6+6q5+wEASARFAAAAAAwOPQMAAAAgiaAIAAAAgEFQBAAAAEASQREAAAAAg6AIAAAAgCSCIgAAAACG/wcw/1Tq9YytAQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "new_count.Brand.plot(kind='bar', figsize=(20, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Brand</th>\n",
       "      <th>Store Number</th>\n",
       "      <th>Store Name</th>\n",
       "      <th>Ownership Type</th>\n",
       "      <th>Street Address</th>\n",
       "      <th>City</th>\n",
       "      <th>Postcode</th>\n",
       "      <th>Phone Number</th>\n",
       "      <th>Timezone</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Latitude</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Country</th>\n",
       "      <th>State/Province</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AD</th>\n",
       "      <th>7</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">AE</th>\n",
       "      <th>AJ</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AZ</th>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>7</td>\n",
       "      <td>20</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DU</th>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>16</td>\n",
       "      <td>50</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FU</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Brand  Store Number  Store Name  Ownership Type  \\\n",
       "Country State/Province                                                    \n",
       "AD      7                   1             1           1               1   \n",
       "AE      AJ                  2             2           2               2   \n",
       "        AZ                 48            48          48              48   \n",
       "        DU                 82            82          82              82   \n",
       "        FU                  2             2           2               2   \n",
       "\n",
       "                        Street Address  City  Postcode  Phone Number  \\\n",
       "Country State/Province                                                 \n",
       "AD      7                            1     1         1             1   \n",
       "AE      AJ                           2     2         0             0   \n",
       "        AZ                          48    48         7            20   \n",
       "        DU                          82    82        16            50   \n",
       "        FU                           2     2         1             0   \n",
       "\n",
       "                        Timezone  Longitude  Latitude  \n",
       "Country State/Province                                 \n",
       "AD      7                      1          1         1  \n",
       "AE      AJ                     2          2         2  \n",
       "        AZ                    48         48        48  \n",
       "        DU                    82         82        82  \n",
       "        FU                     2          2         2  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(['Country', 'State/Province']).count().head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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